Artificial intelligence can analyse myoclonus severity from video footage
Fast, reliable and automatic assessment of the severity of myoclonic jerks from video footage is now possible, thanks to an algorithm using deep convolutional neural network architecture and pretrained models that identify and track keypoints in the human body. Published in Seizure, the study is a joint effort by the Epilepsy Centre at Kuopio University Hospital, the University of Eastern Finland and Neuro Event Labs. Myoclonus refers to brief, involuntary twitching of muscles and it is the most disabling and progressive drug-resistant symptom in patients with progressive myoclonus